The present invention relates generally to information retrieval systems, and more particularly to an information retrieval system and method employing spatially selective features.
Although location is a fundamental, unifying principle humans use to organize their “spatial awareness” of the world, the Internet has failed to deliver high performance spatial search and retrieval capabilities.
Traditional means of finding local content have included reading the local newspapers, searching telephone yellow page directories, listening to the radio, spotting billboards, and seeing local TV announcements or advertising. On the Internet today, some local content can be found using ‘yellow page’ listing services, city content sites, local portals and ISPs.
However, these services offer limited geographic scope and focus mainly on large metropolitan areas. While all of these content sites provide elements of useful information, what is needed is a method to provide a continuum of data across the entire world, and across all categories. As well, it would be advantageous to enable average users to add local content to these databases.
Quickly and easily finding local content on the Internet today is a laborious, convoluted, and inconsistent experience. Internet users are typically required to provide specific Zip code, or other positional information to conduct a search for local content.
Furthermore, in order to find any specific local content, the user has been required to enter a known geographic, postal, or street address to commence a search. This inhibits a user in performing ‘real-world’ searches where one might not know an address or postal code. A system for finding local content at any point within an international geographic extent has not been possible.
Current Internet mapping and local search capabilities are limited to static data, and are restricted to a delimited geographic area, such as a country, and do not provide an optimal geo-location search range for each record. Typically, searches on the Internet are performed by selecting a predetermined classification of information by sub-category(s). The problem is that the resulting size of the search catalogues often requires time-consuming scanning by users through a myriad of categories and/or a large amount of irrelevant results.
Geographic Information Systems (GIS) have, for many years, provided tools to generate, manipulate, and manage spatial data. Government agencies and commercial data vendors use GIS extensively to create and maintain map data used by location services. Vendors provide street-centerline data sets that include address and street name data, which are essential to geo-coding and routing applications. Location services that incorporate GIS tools enable a wide range of spatial transactions that can be delivered in meaningful ways.
Some commercially available database management systems (DBMS) currently include basic spatial data management capabilities, providing limited support to location services. DBMS's specialize in the storage and management of all types of data including geographic data, and are optimized to- store and retrieve data. Although many GIS's rely on DBMS's for this purpose, they are not competitive in terms of performance; flexibility, and scalability without direct access to a robust GIS at their foundation.
Distributing geographic information via the Internet enables real-time display and integration of data from around the world. A natural extension of a traditional desktop GIS, Internet mapping and associated applications have been popularized by various sites that deliver maps to the end user via a browser. However to date, mapping on the Internet has been mainly a cartographic exercise, with minimal capability for true information searching and adding of new content.
Computer desktop mapping systems use the map paradigm to organize data and user interaction. The focus of such systems is the creation of maps, with the map linked to a database containing related information. However, most desktop mapping systems have limited data management, spatial analysis, or customization capabilities.
Computer Aided Design (CAD) systems have evolved to create designs, and buildings plans. CAD systems require that components with fixed characteristics be assembled to create the whole structure. These systems feature few rules to specify how components can, or should be, assembled and include very, limited analytical capabilities. Although some CAD systems have been extended to support maps, they typically have limited utility for managing and analyzing large geographic databases.
Remote sensing is the art and science of making measurements of the earth using sensors such as GPS receivers, or cameras fitted to aircraft or satellites. These sensors collect data in the form of images and data streams and include specialized capabilities for manipulating, analyzing, and visualizing those images.
For the foregoing reasons, there is a need for an improved information retrieval system and method.